Chapter 9 Pipeline and Parallel Recursive and Adaptive Filters
|
|
- Brandon Reed
- 5 years ago
- Views:
Transcription
1 Chpte 9 Ppele d Pllel Recusve d Adptve Fltes Y-Tsug Hwg VLSI DSP Y.T. Hwg 9- Itoducto Ay equed dgtl flte spectum c be eled usg FIR o IIR fltes IIR fltes eque lowe tp ode but hve potetl stblty poblem dptve fltes e used tme vyg systems coeffcets of the dptve dgtl fltes e dpted t ech teto ecusve d dptve fltes cot be esly ppeled o pocessed pllel due to the feedbck loops VLSI DSP Y.T. Hwg 9-
2 Itoducto Pllelg d ppelg ecusve dgtl fltes look hed computto cemetl block pocessg elxed look hed tsfom VLSI DSP Y.T. Hwg 9- Ppele Itelevg Dgtl Fltes Thee foms of ppele televg effcet sgle/mult-chel televg effcet sgle-chel televg effcet mult-chel televg effcet sgle/mult-chel televg cosde st ode LTI ecuso y*yb*u VLSI DSP Y.T. Hwg 9-4
3 Ppele Itelevg Dgtl Fltes smple st ode ecuso b setg - delys c 5-wy televg VLSI DSP Y.T. Hwg 9-5 Sgle/ult-Chel Itelevg Iteto peod s T m T -stge ppeled veso b, whee - ddtol ltches e dded clock peod c be educed by tmes smple peod must be cesed tmes fo coect opeto tmes esclg effectve tto tevl d computg ltecy ems uchged ovehed of - ddtol ltches VLSI DSP Y.T. Hwg 9-6
4 Sgle/ult-Chel Itelevg c, depedet tme sees e opeted o the sme hdwe my coespod to ech cscde stge of lge flte o depedet chels equg detcl flteg opetos lso kow s -slow ccut potetl dwbcks smple te s tmes slowe th the clock te effcet pocesso utlto f depedet computg sees e ot vlble VLSI DSP Y.T. Hwg 9-7 Effcet Sgle Chel Itelevg -step Look hed tsfomto y*yb*u y[*yb*u]b*u teto boud T m T / y *y*b*ub*u teto boud T m T / -step look hed tsfomto y y bu coeffcets c be pe-computed VLSI DSP Y.T. Hwg 9-8
5 Effcet Sgle Chel Itelevg equvlet elto of ufoldg st ode IIR flte tme b equvlet st ode ecuso fte look hed tsfom VLSI DSP Y.T. Hwg 9-9 Effcet Sgle Chel Itelevg -step look hed tsfomto llows sgle sel computto tsfomed to depedet cocuet computtos loop dely s computto s completed cycles teto boud s T m T / hdwe complexty d computg ltecy e lely cesed tmes hghe smplg te th th the ogl gph tl codtos y- - * y,,,., - VLSI DSP Y.T. Hwg 9-
6 Effcet Sgle Chel Itelevg 4 equvlet st ode ecuso fte - step look hed tsfom b ptl schedulg fo 5 VLSI DSP Y.T. Hwg 9- Effcet ult-chel Itelevg Look hed tsfom ppele televg ssume P depedet tme sees chels loop s -stge ppeled the ecuso must be teted Q - tmes, whee P*Q Exmple fo 6, P y y bu bu bu,, ptl schedule fo -chel wth 6 ppele stges obted usg -step LA VLSI DSP Y.T. Hwg 9-
7 Ppelg st Ode IIR Fltes Look hed tsfom toduces ccelg poles d eos f the toduced poles d eos do ot ccel ech othe exctly due to e.g. fte pecso HW lmtto the poles outsde ut ccle wll cuse stblty poblem ppeled elto fo st ode IIR flte s lwys stble povded the ogl s stble decomposto techque to mplemet the o-ecusve poto due to look hed tsfom to cheve logthmc HW complexty cese w..t. the No. of ppele stges VLSI DSP Y.T. Hwg 9- Look Ahed fo st ode IIR Fltes Cosde fst ode flte cots pole t, -stge ppeled veso flte cots dded poles d eos t H becuse the toduced poles hve mgtude lwys less th the flte s lwys stble eve the dded poles e ot exctly cceled out H e ± jπ / VLSI DSP Y.T. Hwg 9-4
8 Look Ahed Ppelg wth Powe of Decomposto No-ecusve pt of powe of -stge ppele s decomposed to log sets of tsfomto b cosde st ode ecusve flte H hs sgle pole t log fte look hed b H ddg - poles d eos t detcl loctos hs poles t loctos, e jπ /, e jπ /,, e j π / VLSI DSP Y.T. Hwg 9-5 Powe of Decomposto The decomposto of the ccelg eos the -th stge mplemets eos locted t e,,,, j π / eques sgle ppeled multplcto opeto depedet of the stge umbe. A totl of log multplcto s eeded VLSI DSP Y.T. Hwg 9-6
9 VLSI DSP Y.T. Hwg 9-7 Powe of Decomposto Powe of Decomposto pole epesetto of st ode ecusve flte b pole eo epesetto of st ode LTI ecusve system wth 8 loop ppelg stges c decomposto bsed ppele mplemetto fo 8 VLSI DSP Y.T. Hwg 9-8 Powe of Decomposto 4 Powe of Decomposto 4 Tme dom explto fo 8 exmple,whee u b y y u b y y f y f y f y u b y y f f f f f f u b f
10 Powe of Decomposto 5 I fte pecso mplemetto, the poles e locted t p Δ / whee Δ coespods to fte pecso eo epesetg the devto becomes sevee whe << ot poblem Δ exct pole-eo ccellto leds to phse d mgtude eo c be educed by cesg the wod legth VLSI DSP Y.T. Hwg 9-9 Iexct pole eo ccellto due to fte pecso mplemetto Powe of Decomposto 6 VLSI DSP Y.T. Hwg 9-
11 Geel Decomposto If p the o-ecusve stges mplemet -, -,, p - eos -stge ppele decomposto exmple H st stge mplemets the eo t - d stge mplemets 4 eos t e d stge mplemets 6 eos t VLSI DSP Y.T. Hwg 9-6, e ± jπ / ± jπ / ± j, e, e ± jπ / 6 ± j5π / 6 pole eo locto of - stge ppeled st ode ecusve flte b decomposto of the eos of the ppeled flte fo decomposto Geel Decomposto VLSI DSP Y.T. Hwg 9-
12 Geel Decomposto A ltetve ppele decomposto H st stge: - d stge: ±j d stge: A ltetve ppele decomposto H ± / st stge: e jπ d stge: d stge: e ± jπ / 6, e ± jπ / e, ±, j, e e ± jπ / 6 ± j5π / 6 ± jπ / 6, 8 e 6, e ± j5π / 6 ± jπ / VLSI DSP Y.T. Hwg 9- Ppelg Hgh Ode IIR Fltes Clusteed look hed tsfoms le hdwe complexty w..t. ppele stges but ot lwys guteed to be stble sctteed look hed tsfoms guteed to be stble hghe hdwe complexty,.e. N* both tsfoms educe to the sme fom the st ode IIR flte cse VLSI DSP Y.T. Hwg 9-4
13 Clusteed Look-Ahed Ppelg Cosde N-th ode dect fom IIR flte H y N N N N b y y b u the smple te s lmted by the thoughput of multplcto d ddto N VLSI DSP Y.T. Hwg 9-5 Clusteed Look-Ahed Ppelg ddg ccelg poles d eos such tht the coeffcets of -,, -- the deomto becomes eo look hed the cluste of pst N outputs by - steps y-, y-,, y-n y-, y--,, y--n the ctcl loop cots dely elemets d sgle multplcto smple te c be cesed by fcto -stge clusteed look-hed ppelg VLSI DSP Y.T. Hwg 9-6
14 Clusteed Look-Ahed Ppelg Cosde ll-pole d ode IIR wth poles t / d /4 ogl tsfe fucto H fo -stge ppelg, the coeffcet of - must be ullfed multply the umeto d deomto by 5/4 - I.e. ddg ccelg pole d eo t -5/4 the tsfomed tsfe fucto H VLSI DSP Y.T. Hwg Clusteed Look-Ahed Ppelg 4 -stge ppelg multply the umeto d deomto by 5/4-9/6-5 the tsfomed tsfe fucto H geel fom of multplyg fctos, whee, fo,,, N N k, k k fo > VLSI DSP Y.T. Hwg 9-8
15 Clusteed Look-Ahed Ppelg 5 Hdwe mplemetto complexty coeffcets of the fltes e pe-computed off-le umeto o-ecusve pt eques N PYs deomto ecusve pt eques N PYs totl N N multplctos le HW mplemetto complexty Flte stblty poblem ddg poles my le outsde the ut ccle exmple: ssume the d ode IIR hs poles t.5 d.75 -stge ppelg toduce ddtol pole t -.5 VLSI DSP Y.T. Hwg 9-9 Clusteed Look-Ahed Ppelg 6 pole eo epesetto of stble d ode ecusve flte b poles & eos fte - stge ppelg usg clusteed look hed c poles & eos fte - stge ppelg usg clusteed look hed VLSI DSP Y.T. Hwg 9-
16 Clusteed Look-Ahed Ppelg 7 Flte stblty poblem cot. -stge ppelg toduce two ddtol poles t.65 ± j.89 ote tht the ogl flte s stble! VLSI DSP Y.T. Hwg 9- Stble Clusteed Look hed Flte Desg Cosde stble ecusve dgtl flte H N H D N P N P D P Q P epesets supefluous poles eeded to cete the desed ppele dely fo > c some ctcl dely, the flte s lwys stble umecl sech methods e eeded to obt optml ppelg level d P Exmple: cosde H c 5 d fo 6, H VLSI DSP Y.T. Hwg 9-
17 Stble Clusteed Look hed Flte Desg ogl poles b poles & eos of 6-stge ppeled flte usg stble clusteed look hed whe the o. of deomto multples s lge, ppeled flte suffes fom lge oud-off ose the deomto cot be decomposed ode to mt level of ppelg VLSI DSP Y.T. Hwg 9- Sctteed Look Ahed Ppelg The deomto of H s tsfomed to cotg N tems, Z -, Z -,, Z -N equvletly, y s computed tems of N pst sctteed sttes y-, y-,, y-n fo ech pole, - ccelg poles d eos e toduced wth equl gul spcg sme dstce fom the og s tht of the ogl pole e.g. f the ogl pole s p jπk / dded poles d eos e pe, fo k,,, VLSI DSP Y.T. Hwg 9-4
18 VLSI DSP Y.T. Hwg 9-5 Sctteed Look Ahed Ppelg Sctteed Look Ahed Ppelg Assume the deomto of H c be fctoed s fte sctteed look-hed tsfom cosde the d ode flte, fo N p D ' ' / / N k k j N k k j Z D N p e p e N D N H π π 6 4 H H VLSI DSP Y.T. Hwg 9-6 Sctteed Look Ahed Ppelg Sctteed Look Ahed Ppelg Cosde the d-ode flte wth complex cojugte poles t fo -stge ppelg whe θπ/, oly pole & eo t e dded jθ e ± cos H θ cos cos cos cos H θ θ θ θ H
19 VLSI DSP Y.T. Hwg 9-7 Sctteed Look Ahed Ppelg 4 Sctteed Look Ahed Ppelg 4 Cosde the d-ode flte wth poles t, fo -stge ppelg ddg poles t H / /, π π j j e e ± ± 6 4 H VLSI DSP Y.T. Hwg 9-8 Sctteed Look Ahed Ppelg 5 Sctteed Look Ahed Ppelg 5 Pole eo epesetto of -stge ppeled equvlet stble flte usg sctteed look hed
20 Powe of Decomposto Sctteed Look Ahed Scheme The multplcto complexty sctteed look hed tsfom o-ecusve poto : N ecusve poto s : N much gete th tht clusteed look hed scheme cosde ecusve flte H ' N N b N D N by multplyg both umeto d deomto VLSI DSP Y.T. Hwg 9-9 Powe of Decomposto Fo -stge ppelg H N N b ' N N [ ][ ] N' D' the deomto cots tems of -, -4,, -N subsequet tsfoms c be ppled to obt 4,8 d 6 stge ppeled mplemettos log sets of tsfoms e eeded to cheve - stge ppelg ech tsfom double the speed but lso cese the hdwe complexty by N VLSI DSP Y.T. Hwg 9-4
21 Powe of Decomposto Applyg log - sets of tsfoms leds to -stge ppelg eques NN* log multplctos logthmc complexty w..t. speed up totl umbe of delys N*log N delys e used the o-ecusve poto N*log delys e equed to ppele ech N*log multples by stges VLSI DSP Y.T. Hwg 9-4 Powe of Decomposto 4 N- poles d eos e dded N- eos e decomposed d mplemeted log stges st stge eles N-th ode oecusve secto followg stges mplemets N, 4N,, N/- ode o-ecusve sectos ech secto eques N multplcto due to the symmety of coeffcets depedet of the ode of the secto VLSI DSP Y.T. Hwg 9-4
22 Powe of Decomposto 5 Cosde d-ode ecusve flte exmple H Y U b b b cosθ the poles e locted t the ppeled fucto H cos θ jθ e ± the poles e locted t b log cos θ e ± j θ π /,,,,, mplemetto complexty s log 5 multplctos VLSI DSP Y.T. Hwg 9-4 Powe of Decomposto 6 pole dgm of the d ode flte b poles & eos of the ppeled d ode flte wth 8 loop ppelg stges c decomposto of poles d eos of the ppeled flte VLSI DSP Y.T. Hwg 9-44
23 Powe of Decomposto 7 Implemetto of the ogl d the ppeled sctteed look-hed ecusve fltes VLSI DSP Y.T. Hwg 9-45 Sctteed LA Ppelg wth Geel decomposto Fo N-th ode flte wth levels of ppelg N- ccelg eos fo p decomposto the st stge mplemets N - eos the d stge mplemets N - eos the Pth stge mplemets N p- p - eos the o-ecusve poto eques N delys d N P multples geeto decomposto of hgh ode IIR flte decompose to cscde of st ode sectos pply geel decomposto to ech st ode secto VLSI DSP Y.T. Hwg 9-46
24 Pllel Pocessg fo IIR Fltes st ode IIR flte cse H whee y yu fo 4-pllel chtectue mplemetto y4 4 y u uuu by substtutg 4k y4k4 4 y4k u4k u4ku4ku4k pole of the ogl system s t pole of the pllel system s t 4 pole s moved towd the og mpoved obustess to the oud-off eo VLSI DSP Y.T. Hwg 9-47 Pllel Pocessg fo IIR Fltes Note tht ppeled pocessg cse, ccelg poles d eos e toduced substtutg wth 4k4, 4k5, 4k6, 4k7 ledg to 4 pllel pocessg blocks VLSI DSP Y.T. Hwg 9-48
25 Pllel Pocessg fo IIR Fltes eque L AC opetos oe dely elemet epesets L smple delys VLSI DSP Y.T. Hwg 9-49 Pllel Pocessg fo IIR Fltes 4 Icemetl block pocessg use y4k to compute y4k,.e. y4k y4k u4k d the use y4k to compute y4k, the y4k the hdwe complexty s educed fom L to L- cesed computto tme fo y4k, y4k, y4k VLSI DSP Y.T. Hwg 9-5
26 Pllel Pocessg fo IIR Fltes 5 Icemetl block flte stuctue wth L 4 VLSI DSP Y.T. Hwg 9-5 Pllel Pocessg fo IIR Fltes 6 A secod ode IIR exmple fo block pocessg H y y y f, 4 8 whee u u u -pllel system compute yk d yk4 usg yk d yk fo yk, yk yk -stge clusteed LA fo yk, yk yk4 -stge clusteed LA VLSI DSP Y.T. Hwg 9-5
27 Pllel Pocessg fo IIR Fltes 7 & -stge clusteed look hed 5 y y y f y y f y f y y 4 f y f f -loop updte equto yk yk yk f k yk 4 yk yk f k f k 5 4 f k f k 4 VLSI DSP Y.T. Hwg 9-5 Pllel Pocessg fo IIR Fltes 8 Pole eo plots of the tsfe fucto loop updte fo block se eltoshp of ecuso outputs VLSI DSP Y.T. Hwg 9-54
28 Pllel Pocessg fo IIR Fltes 9 yk c be obted cemetlly 5 y k yk yk f k 4 8 VLSI DSP Y.T. Hwg 9-55 Commets The ogl system hs poles t / d /4 tsfomed system 5 yk 57 yk the mtx hs egevlues / d /4 the pllel system s moe stble the pllel system hs the sme umbe of poles s the ogl system hdwe complexty yk yk fo d ode IIR flte N L [L- L-] 4 L- 7L - PY opetos f f VLSI DSP Y.T. Hwg 9-56
29 Combed Pllel & Ppelg Pocessg To cheve speed up L L s the block se d s the o. of ppelg stge fo H/- - wth 4 d L H s st ode loop updte equto s equed d the othe two c be computed cemetlly 4 loop cots 4 dely elemets L yk yk VLSI DSP Y.T. Hwg 9-57 Combed Pllel & Ppelg Pocessg -step look hed tsfom y y u y substtutg k yk 8 5 yk uk uk 4 uk 7 yk u uk uk 5 uk 8 k 6 u u uk uk 6 uk 9 uk uk uk 6 f f k 9 f k VLSI DSP Y.T. Hwg 9-58
30 Combed Pllel & Ppelg Pocessg Whee f k f k uk uk uk f k 9 f k VLSI DSP Y.T. Hwg 9-59 Commets Combed Pllel & Ppelg Pocessg 4 hs 4 poles, -, j, -j decomposto s used fo the o-ecusve poto multplcto complexty s L-log d ode flte exmple wth L d H loop updte opetos ogl poles /, /4 ew poles ±/, ±/4 VLSI DSP Y.T. Hwg 9-6
31 Commets Systemtc ppoch to compute pole loctos wte loop updte equtos usg L-level look hed wte the stte spce epesetto of the pllel ppeled flte, whee stte mtx A N N compute the eevlues λ of mtx A, I N N poles of the ew pllel ppeled system coespod to the -th oots of the egevlues of A, λ VLSI DSP Y.T. Hwg 9-6 Low Powe IIR Flte Desg Pllel d ppeled pocessg c be used fo low powe desg cosde 4-th ode Chebyshev low-pss flte 4.86 H ssume multple cpctce s domt ssume Vdd 5V d Vt v usg sctteed look hed wth powe of decomposto VLSI DSP Y.T. Hwg 9-6
32 Ppeled pocessg to educe powe 4-level ppelble tsfe fucto N/D N D ppeled desg set delys to the ecusve shote ctcl pth fte etmg smlle mout of chgg/dschgg cpctce ech ppele stge use lowe powe supply yet mt the ogl speed the ppeled suppled βv, wth β < 4 8 VLSI DSP Y.T. Hwg 9-6 Ppeled pocessg to educe powe popgto dely sequetl system s 4-level ppeled system β.476 d ew Vdd.8V powe dsspto T pd T pd C k V C ch g e dd ch g e Vdd Vt k5 Cch g e 5β 4 k5β 5 the smple peod s equl to T pd C sequetl system s P 4-level ppeled system P seq pp C seq totl T pd pp totl 5 m.8 T pd seq C m pp 5 C f s.8 f s VLSI DSP Y.T. Hwg 9-64
33 Ppeled pocessg to educe powe Powe to umbe of multplctos, m seq 5, m pp P Rto P pp seq Exmple: secod ode IIR flte 5 y y y u u u 4 8 VLSI DSP Y.T. Hwg 9-65 Pllel pocessg to educe the powe -pllel flte desg outputs pe clock cycle clock cycle c be thee tmes the smple cycle the ctcl pth of the sequetl flte s PY Add feedfowd pt of the ppeled flte desg s etmed VLSI DSP Y.T. Hwg 9-66
34 Pllel pocessg to educe the powe Popgto dely The ctcl pth of the pllel desg s PY Add ssume the chge/dschge cpctces d the delys e domted by the multples ssume the pllel flte suppled βv, wth β < d the theshold voltge V t.6v popgto dely clock cycle fo sequetl flte s CV Tseq k V V t popgto dely clock cycle fo pllel flte s T C βv p k βv Vt VLSI DSP Y.T. Hwg 9-67 Pllel pocessg to educe the powe V βv Choose T p T seq V V βv we get β.467 d βv.65v powe cosumpto P P seq p C C P Rto P commets p seq V f s βv 4β fs 4β C 9.6% t V t the pllel o ppeled desg c be used ethe to cheve hgh speed o low powe opetos VLSI DSP Y.T. Hwg 9-68 V f s
35 Ppeled Adptve Dgtl Fltes Adptve dgtl fltes e dffcult becuse pesece of log feedbck loop look hed tsfom leds to pohbtvely lge hdwe ovehed ote tht look hed tsfom mts exct putoutput mppg sce coeffcets of the dptve fltes cotue to chge exct put-output mppg s ot ecessy dptve flte mesuemet dexes ms-djustmet eo dptto tme costt VLSI DSP Y.T. Hwg 9-69 Ppeled Adptve Dgtl Fltes Relxed look-hed tsfom ms to ppele dptve flte wth lttle hdwe ovehed d t the expese of mgl degdto of dptto behvo poduct elxto sum elxto dely elxto the dptto behvo of the ppeled dptve fltes should be lyed usg stochstc techques VLSI DSP Y.T. Hwg 9-7
36 VLSI DSP Y.T. Hwg 9-7 Relxed Look Ahed Relxed Look Ahed Cosde the st ode tme vyg ecuso yyu, whee coeffcet s tme vyg usg look hed tsfom fo 4, the teto peod s lmted to T m T /4 ude cet ccumstces, we c substtute ppoxmto expessos to smplfy the tems the RHS [ ] u u j y y j VLSI DSP Y.T. Hwg 9-7 Relxed Look hed Tsfom Relxed Look hed Tsfom A 4-level look hed ppeled st ode
37 VLSI DSP Y.T. Hwg 9-7 Poduct Relxto Poduct Relxto Assumptos s close to d -ε, whee ε s close to eo f u s close to eo, the N ε ε [ ] j u y y u u j VLSI DSP Y.T. Hwg 9-74 Poduct Relxto Poduct Relxto A 4-level poduct elxed lookhed ppeled st ode ecuso
38 VLSI DSP Y.T. Hwg 9-75 Poduct Relxto Poduct Relxto Aothe ppoxmto s ssumed to be close to j u y y j VLSI DSP Y.T. Hwg 9-76 Sum Relxto Sum Relxto If the put u ves slowly ove cycles f u s close to eo, the u u [ ] u y u u j y y j u y y
39 Sum Relxto A 4-level sum-elxed look-hed ppeled stode ecuso VLSI DSP Y.T. Hwg 9-77 Dely Relxto Cosde the ecuso yy-u -level look-hed ppeled veso y y u dely elxto volves the use of delyed put u- d delyed coeffcet - ssume the poduct u s moe o less costt ove smples esoble ssumpto fo sttoy o slowly vyg poduct u y y ' u ' VLSI DSP Y.T. Hwg 9-78
40 VLSI DSP Y.T. Hwg 9-79 Commets of elxto techques Commets of elxto techques Thee elxto techques c be ppled dvdully o dffeet combtos to deve ch vety of chtectues ech deved chtectue hs dffeet covegece chctestcs the elxed look-hed s tsfom the stochstc sese VLSI DSP Y.T. Hwg 9-8 Ppeled LS Adptve Flte Ppeled LS Adptve Flte LS lgothm ecusve loops the LS chtectue weght updte loop eo feedbck loop dect look hed s the dely the weght updte loop ˆ U e W W U W d d d e T μ U e W U e W W μ μ
41 VLSI DSP Y.T. Hwg 9-8 Ppeled LS Adptve Flte Ppeled LS Adptve Flte By dely elxto ssume the gdet estmte eu ves slowly the hdwe complexty s N - ACs futhe sum elxto tkg oly the fst sum tems, whee U e W U e W W μ μ ] [ ' U U e W d U W d e T T μ VLSI DSP Y.T. Hwg 9-8 Ppeled LS Adptve Flte Ppeled LS Adptve Flte Assume μ s suffcetly smll d eplcg W- - by W- U W d e T
Chapter 17. Least Square Regression
The Islmc Uvest of Gz Fcult of Egeeg Cvl Egeeg Deptmet Numecl Alss ECIV 336 Chpte 7 Lest que Regesso Assocte Pof. Mze Abultef Cvl Egeeg Deptmet, The Islmc Uvest of Gz Pt 5 - CURVE FITTING Descbes techques
More informationChapter Linear Regression
Chpte 6.3 Le Regesso Afte edg ths chpte, ou should be ble to. defe egesso,. use sevel mmzg of esdul cte to choose the ght cteo, 3. deve the costts of le egesso model bsed o lest sques method cteo,. use
More informationGauss-Quadrature for Fourier-Coefficients
Copote Techology Guss-Qudtue o Foue-Coecets A. Glg. Hezog. Pth P. Retop d U. Weve Cotet: The tusve method The o-tusve method Adptve Guss qudtue Embeddg to optmzto Applcto u ü tee Gebuch / Copyght Semes
More informationDescribes techniques to fit curves (curve fitting) to discrete data to obtain intermediate estimates.
CURVE FITTING Descbes techques to ft cuves (cuve fttg) to dscete dt to obt temedte estmtes. Thee e two geel ppoches fo cuve fttg: Regesso: Dt ehbt sgfct degee of sctte. The stteg s to deve sgle cuve tht
More informationSOLVING SYSTEMS OF EQUATIONS, DIRECT METHODS
ELM Numecl Alyss D Muhem Mecmek SOLVING SYSTEMS OF EQUATIONS DIRECT METHODS ELM Numecl Alyss Some of the cotets e dopted fom Luee V. Fusett Appled Numecl Alyss usg MATLAB. Petce Hll Ic. 999 ELM Numecl
More information2. Elementary Linear Algebra Problems
. Eleety e lge Pole. BS: B e lge Suoute (Pog pge wth PCK) Su of veto opoet:. Coputto y f- poe: () () () (3) N 3 4 5 3 6 4 7 8 Full y tee Depth te tep log()n Veto updte the f- poe wth N : ) ( ) ( ) ( )
More informationSOME REMARKS ON HORIZONTAL, SLANT, PARABOLIC AND POLYNOMIAL ASYMPTOTE
D I D A C T I C S O F A T H E A T I C S No (4) 3 SOE REARKS ON HORIZONTAL, SLANT, PARABOLIC AND POLYNOIAL ASYPTOTE Tdeusz Jszk Abstct I the techg o clculus, we cosde hozotl d slt symptote I ths ppe the
More informationANOTHER INTEGER NUMBER ALGORITHM TO SOLVE LINEAR EQUATIONS (USING CONGRUENCY)
ANOTHER INTEGER NUMBER ALGORITHM TO SOLVE LINEAR EQUATIONS (USING CONGRUENCY) Floet Smdche, Ph D Aocte Pofeo Ch of Deptmet of Mth & Scece Uvety of New Mexco 2 College Rod Gllup, NM 873, USA E-ml: md@um.edu
More informationMTH 146 Class 7 Notes
7.7- Approxmte Itegrto Motvto: MTH 46 Clss 7 Notes I secto 7.5 we lered tht some defte tegrls, lke x e dx, cot e wrtte terms of elemetry fuctos. So, good questo to sk would e: How c oe clculte somethg
More information6.6 The Marquardt Algorithm
6.6 The Mqudt Algothm lmttons of the gdent nd Tylo expnson methods ecstng the Tylo expnson n tems of ch-sque devtves ecstng the gdent sech nto n tetve mtx fomlsm Mqudt's lgothm utomtclly combnes the gdent
More informationInsurance Risk EC for XL contracts with an inflation stability clause
suce Rs E fo L cotcts wth flto stlt cluse 40 th t. AT oll. Mdd Jue 9-0 opght 008 FR Belgum V "FRGlol". Aged upemposed flto / stlt cluse suce Rs olutos o-lfe Rs / tdd ppoch o-lfe Rs / tochstc ppoch goss
More informationLattice planes. Lattice planes are usually specified by giving their Miller indices in parentheses: (h,k,l)
Ltte ples Se the epol ltte of smple u ltte s g smple u ltte d the Mlle des e the oodtes of eto oml to the ples, the use s ey smple lttes wth u symmety. Ltte ples e usully spefed y gg the Mlle des petheses:
More information( m is the length of columns of A ) spanned by the columns of A : . Select those columns of B that contain a pivot; say those are Bi
Assgmet /MATH 47/Wte Due: Thusday Jauay The poblems to solve ae umbeed [] to [] below Fst some explaatoy otes Fdg a bass of the colum-space of a max ad povg that the colum ak (dmeso of the colum space)
More informationBINOMIAL THEOREM SOLUTION. 1. (D) n. = (C 0 + C 1 x +C 2 x C n x n ) (1+ x+ x 2 +.)
BINOMIAL THEOREM SOLUTION. (D) ( + + +... + ) (+ + +.) The coefficiet of + + + +... + fo. Moeove coefficiet of is + + + +... + if >. So. (B)... e!!!! The equied coefficiet coefficiet of i e -.!...!. (A),
More information= y and Normed Linear Spaces
304-50 LINER SYSTEMS Lectue 8: Solutos to = ad Nomed Lea Spaces 73 Fdg N To fd N, we eed to chaacteze all solutos to = 0 Recall that ow opeatos peseve N, so that = 0 = 0 We ca solve = 0 ecusvel backwads
More informationEquidistribution in Sharing Games
Ope Joul of Dscete Mthemtcs, 4, 4, 9-8 Publshed Ole Juy 4 (http://wwwscpog/oul/odm http://dxdoog/436/odm443 Equdstbuto Shg Gmes Clos D Ade, Emlo Gómez Deptmet d Àlgeb Geomet, Uvestt de Bcelo, Bcelo, Sp
More informationGCE AS/A Level MATHEMATICS GCE AS/A Level FURTHER MATHEMATICS
GCE AS/A Level MATHEMATICS GCE AS/A Level FURTHER MATHEMATICS FORMULA BOOKLET Fom Septembe 07 Issued 07 Mesuto Pue Mthemtcs Sufce e of sphee = 4 Ae of cuved sufce of coe = slt heght Athmetc Sees S l d
More informationOptimality of Strategies for Collapsing Expanded Random Variables In a Simple Random Sample Ed Stanek
Optmlt of Strteges for Collpsg Expe Rom Vrles Smple Rom Smple E Stek troucto We revew the propertes of prectors of ler comtos of rom vrles se o rom vrles su-spce of the orgl rom vrles prtculr, we ttempt
More informationRECAPITULATION & CONDITIONAL PROBABILITY. Number of favourable events n E Total number of elementary events n S
Fomulae Fo u Pobablty By OP Gupta [Ida Awad We, +91-9650 350 480] Impotat Tems, Deftos & Fomulae 01 Bascs Of Pobablty: Let S ad E be the sample space ad a evet a expemet espectvely Numbe of favouable evets
More informationXII. Addition of many identical spins
XII. Addto of may detcal sps XII.. ymmetc goup ymmetc goup s the goup of all possble pemutatos of obects. I total! elemets cludg detty opeato. Each pemutato s a poduct of a ceta fte umbe of pawse taspostos.
More informationCBSE , ˆj. cos CBSE_2015_SET-1. SECTION A 1. Given that a 2iˆ ˆj. We need to find. 3. Consider the vector equation of the plane.
CBSE CBSE SET- SECTION. Gv tht d W d to fd 7 7 Hc, 7 7 7. Lt,. W ow tht.. Thus,. Cosd th vcto quto of th pl.. z. - + z = - + z = Thus th Cts quto of th pl s - + z = Lt d th dstc tw th pot,, - to th pl.
More informationThe z-transform. LTI System description. Prof. Siripong Potisuk
The -Trsform Prof. Srpog Potsuk LTI System descrpto Prevous bss fucto: ut smple or DT mpulse The put sequece s represeted s ler combto of shfted DT mpulses. The respose s gve by covoluto sum of the put
More informationCapacitance Calculations
Cpctce Clcultos Atoo Clos M. de Queoz cmq@ufj.b Abstct Ths documet descbes clculto methods fo dstbuted cpctces of objects wth sevel ptcul shpes, d methods fo the evluto of the electc felds d foces. It
More informationArea and the Definite Integral. Area under Curve. The Partition. y f (x) We want to find the area under f (x) on [ a, b ]
Are d the Defte Itegrl 1 Are uder Curve We wt to fd the re uder f (x) o [, ] y f (x) x The Prtto We eg y prttog the tervl [, ] to smller su-tervls x 0 x 1 x x - x -1 x 1 The Bsc Ide We the crete rectgles
More information5 - Determinants. r r. r r. r r. r s r = + det det det
5 - Detemts Assote wth y sque mtx A thee s ume lle the etemt of A eote A o et A. Oe wy to efe the etemt, ths futo fom the set of ll mtes to the set of el umes, s y the followg thee popetes. All mtes elow
More informationChapter 7. Kleene s Theorem. 7.1 Kleene s Theorem. The following theorem is the most important and fundamental result in the theory of FA s:
Chpte 7 Kleene s Theoem 7.1 Kleene s Theoem The following theoem is the most impotnt nd fundmentl esult in the theoy of FA s: Theoem 6 Any lnguge tht cn e defined y eithe egul expession, o finite utomt,
More informationChapter 28 Sources of Magnetic Field
Chpte 8 Souces of Mgnetic Field - Mgnetic Field of Moving Chge - Mgnetic Field of Cuent Element - Mgnetic Field of Stight Cuent-Cying Conducto - Foce Between Pllel Conductos - Mgnetic Field of Cicul Cuent
More informationICS141: Discrete Mathematics for Computer Science I
Uversty o Hw ICS: Dscrete Mthemtcs or Computer Scece I Dept. Iormto & Computer Sc., Uversty o Hw J Stelovsy bsed o sldes by Dr. Be d Dr. Stll Orgls by Dr. M. P. Fr d Dr. J.L. Gross Provded by McGrw-Hll
More informationANSWER KEY PHYSICS. Workdone X
ANSWER KEY PHYSICS 6 6 6 7 7 7 9 9 9 0 0 0 CHEMISTRY 6 6 6 7 7 7 9 9 9 0 0 60 MATHEMATICS 6 66 7 76 6 6 67 7 77 7 6 6 7 7 6 69 7 79 9 6 70 7 0 90 PHYSICS F L l. l A Y l A ;( A R L L A. W = (/ lod etesio
More informationChapter #2 EEE State Space Analysis and Controller Design
Chpte EEE8- Chpte # EEE8- Stte Spce Al d Cotolle Deg Itodcto to tte pce Obevblt/Cotollblt Modle ede: D D Go - d.go@cl.c.k /4 Chpte EEE8-. Itodcto Ae tht we hve th ode te: f, ', '',.... Ve dffclt to td
More informationElectric Potential. and Equipotentials
Electic Potentil nd Euipotentils U Electicl Potentil Review: W wok done y foce in going fom to long pth. l d E dl F W dl F θ Δ l d E W U U U Δ Δ l d E W U U U U potentil enegy electic potentil Potentil
More information12 Iterative Methods. Linear Systems: Gauss-Seidel Nonlinear Systems Case Study: Chemical Reactions
HK Km Slghtly moded //9 /8/6 Frstly wrtte t Mrch 5 Itertve Methods er Systems: Guss-Sedel Noler Systems Cse Study: Chemcl Rectos Itertve or ppromte methods or systems o equtos cosst o guessg vlue d the
More informationThis immediately suggests an inverse-square law for a "piece" of current along the line.
Electomgnetic Theoy (EMT) Pof Rui, UNC Asheville, doctophys on YouTube Chpte T Notes The iot-svt Lw T nvese-sque Lw fo Mgnetism Compe the mgnitude of the electic field t distnce wy fom n infinite line
More informationLevel-2 BLAS. Matrix-Vector operations with O(n 2 ) operations (sequentially) BLAS-Notation: S --- single precision G E general matrix M V --- vector
evel-2 BS trx-vector opertos wth 2 opertos sequetlly BS-Notto: S --- sgle precso G E geerl mtrx V --- vector defes SGEV, mtrx-vector product: r y r α x β r y ther evel-2 BS: Solvg trgulr system x wth trgulr
More informationChapter 2 Intro to Math Techniques for Quantum Mechanics
Wter 3 Chem 356: Itroductory Qutum Mechcs Chpter Itro to Mth Techques for Qutum Mechcs... Itro to dfferetl equtos... Boudry Codtos... 5 Prtl dfferetl equtos d seprto of vrbles... 5 Itroducto to Sttstcs...
More informationData Structures. Element Uniqueness Problem. Hash Tables. Example. Hash Tables. Dana Shapira. 19 x 1. ) h(x 4. ) h(x 2. ) h(x 3. h(x 1. x 4. x 2.
Element Uniqueness Poblem Dt Stuctues Let x,..., xn < m Detemine whethe thee exist i j such tht x i =x j Sot Algoithm Bucket Sot Dn Shpi Hsh Tbles fo (i=;i
More informationThe formulae in this booklet have been arranged according to the unit in which they are first
Fomule Booklet Fomule Booklet The fomule ths ooklet hve ee ge og to the ut whh the e fst toue. Thus te sttg ut m e eque to use the fomule tht wee toue peeg ut e.g. tes sttg C mght e epete to use fomule
More informationCS473-Algorithms I. Lecture 3. Solving Recurrences. Cevdet Aykanat - Bilkent University Computer Engineering Department
CS473-Algorthms I Lecture 3 Solvg Recurreces Cevdet Aykt - Blket Uversty Computer Egeerg Deprtmet Solvg Recurreces The lyss of merge sort Lecture requred us to solve recurrece. Recurreces re lke solvg
More informationIn Calculus I you learned an approximation method using a Riemann sum. Recall that the Riemann sum is
Mth Sprg 08 L Approxmtg Dete Itegrls I Itroducto We hve studed severl methods tht llow us to d the exct vlues o dete tegrls However, there re some cses whch t s ot possle to evlute dete tegrl exctly I
More informationLecture 10: Condensed matter systems
Lectue 0: Codesed matte systems Itoducg matte ts codesed state.! Ams: " Idstgushable patcles ad the quatum atue of matte: # Cosequeces # Revew of deal gas etopy # Femos ad Bosos " Quatum statstcs. # Occupato
More informationGCE AS and A Level MATHEMATICS FORMULA BOOKLET. From September Issued WJEC CBAC Ltd.
GCE AS d A Level MATHEMATICS FORMULA BOOKLET Fom Septeme 07 Issued 07 Pue Mthemtcs Mesuto Suce e o sphee = 4 Ae o cuved suce o coe = heght slt Athmetc Sees S = + l = [ + d] Geometc Sees S = S = o < Summtos
More informationCOMP 465: Data Mining More on PageRank
COMP 465: Dt Mnng Moe on PgeRnk Sldes Adpted Fo: www.ds.og (Mnng Mssve Dtsets) Powe Iteton: Set = 1/ 1: = 2: = Goto 1 Exple: d 1/3 1/3 5/12 9/24 6/15 = 1/3 3/6 1/3 11/24 6/15 1/3 1/6 3/12 1/6 3/15 Iteton
More informationPROGRESSION AND SERIES
INTRODUCTION PROGRESSION AND SERIES A gemet of umbes {,,,,, } ccodig to some well defied ule o set of ules is clled sequece Moe pecisely, we my defie sequece s fuctio whose domi is some subset of set of
More informationCourse Updates. Reminders: 1) Assignment #8 available. 2) Chapter 28 this week.
Couse Updtes http://www.phys.hwii.edu/~vne/phys7-sp1/physics7.html Remindes: 1) Assignment #8 vilble ) Chpte 8 this week Lectue 3 iot-svt s Lw (Continued) θ d θ P R R θ R d θ d Mgnetic Fields fom long
More informationLecture 3-4 Solutions of System of Linear Equations
Lecture - Solutos of System of Ler Equtos Numerc Ler Alger Revew of vectorsd mtrces System of Ler Equtos Guss Elmto (drect solver) LU Decomposto Guss-Sedel method (tertve solver) VECTORS,,, colum vector
More informationChapter Unary Matrix Operations
Chpter 04.04 Ury trx Opertos After redg ths chpter, you should be ble to:. kow wht ury opertos mes,. fd the trspose of squre mtrx d t s reltoshp to symmetrc mtrces,. fd the trce of mtrx, d 4. fd the ermt
More informationAdvanced Algorithmic Problem Solving Le 3 Arithmetic. Fredrik Heintz Dept of Computer and Information Science Linköping University
Advced Algorthmc Prolem Solvg Le Arthmetc Fredrk Hetz Dept of Computer d Iformto Scece Lköpg Uversty Overvew Arthmetc Iteger multplcto Krtsu s lgorthm Multplcto of polyomls Fst Fourer Trsform Systems of
More informationGeneral Physics II. number of field lines/area. for whole surface: for continuous surface is a whole surface
Genel Physics II Chpte 3: Guss w We now wnt to quickly discuss one of the moe useful tools fo clculting the electic field, nmely Guss lw. In ode to undestnd Guss s lw, it seems we need to know the concept
More informationAS and A Level Further Mathematics B (MEI)
fod Cmbdge d RSA *3369600* AS d A evel Futhe Mthemtcs B (MEI) The fomto ths booklet s fo the use of cddtes followg the Advced Subsd Futhe Mthemtcs B (MEI)(H635) o the Advced GCE Futhe Mthemtcs B (MEI)
More informationDATA FITTING. Intensive Computation 2013/2014. Annalisa Massini
DATA FITTING Itesve Computto 3/4 Als Mss Dt fttg Dt fttg cocers the problem of fttg dscrete dt to obt termedte estmtes. There re two geerl pproches two curve fttg: Iterpolto Dt s ver precse. The strteg
More informationPhysics 11b Lecture #11
Physics 11b Lectue #11 Mgnetic Fields Souces of the Mgnetic Field S&J Chpte 9, 3 Wht We Did Lst Time Mgnetic fields e simil to electic fields Only diffeence: no single mgnetic pole Loentz foce Moving chge
More informationChapter 7. Bounds for weighted sums of Random Variables
Chpter 7. Bouds for weghted sums of Rdom Vrbles 7. Itroducto Let d 2 be two depedet rdom vrbles hvg commo dstrbuto fucto. Htczeko (998 d Hu d L (2000 vestgted the Rylegh dstrbuto d obted some results bout
More informationThe formulae in this booklet have been arranged according to the unit in which they are first
Fomule Booklet Fomule Booklet The fomule ths ooklet hve ee ge ccog to the ut whch the e fst touce. Thus cte sttg ut m e eque to use the fomule tht wee touce peceg ut e.g. ctes sttg C mght e epecte to use
More informationProfessor Wei Zhu. 1. Sampling from the Normal Population
AMS570 Pofesso We Zhu. Samplg fom the Nomal Populato *Example: We wsh to estmate the dstbuto of heghts of adult US male. It s beleved that the heght of adult US male follows a omal dstbuto N(, ) Def. Smple
More informationMathematical Statistics
7 75 Ode Sttistics The ode sttistics e the items o the dom smple ed o odeed i mitude om the smllest to the lest Recetl the impotce o ode sttistics hs icesed owi to the moe equet use o opmetic ieeces d
More informationDifference Sets of Null Density Subsets of
dvces Pue Mthetcs 95-99 http://ddoog/436/p37 Pulshed Ole M (http://wwwscrpog/oul/p) Dffeece Sets of Null Dest Susets of Dwoud hd Dsted M Hosse Deptet of Mthetcs Uvest of Gul Rsht I El: hd@gulc h@googlelco
More informationAdvanced Higher Maths: Formulae
: Fomule Gee (G): Fomule you bsolutely must memoise i ode to pss Advced Highe mths. Remembe you get o fomul sheet t ll i the em! Ambe (A): You do t hve to memoise these fomule, s it is possible to deive
More informationCh 26 - Capacitance! What s Next! Review! Lab this week!
Ch 26 - Cpcitnce! Wht s Next! Cpcitnce" One week unit tht hs oth theoeticl n pcticl pplictions! Cuent & Resistnce" Moving chges, finlly!! Diect Cuent Cicuits! Pcticl pplictions of ll the stuff tht we ve
More information8. SIMPLE LINEAR REGRESSION. Stupid is forever, ignorance can be fixed.
CIVL 33 Appomto d Ucett J.W. Hule, R.W. Mee 8. IMPLE LINEAR REGREION tupd s foeve, goce c be fed. Do Wood uppose we e gve set of obsevtos (, ) tht we beleve to be elted s f(): Lookg t the plot t ppes tht
More informationSpectral Continuity: (p, r) - Α P And (p, k) - Q
IOSR Joul of Mthemtcs (IOSR-JM) e-issn: 2278-5728, p-issn: 2319-765X Volume 11, Issue 1 Ve 1 (J - Feb 215), PP 13-18 wwwosjoulsog Spectl Cotuty: (p, ) - Α P Ad (p, k) - Q D Sethl Kum 1 d P Mhesw Nk 2 1
More informationAvailable online through
Avlble ole through wwwmfo FIXED POINTS FOR NON-SELF MAPPINGS ON CONEX ECTOR METRIC SPACES Susht Kumr Moht* Deprtmet of Mthemtcs West Begl Stte Uverst Brst 4 PrgsNorth) Kolt 76 West Begl Id E-ml: smwbes@yhoo
More informationPubH 7405: REGRESSION ANALYSIS REGRESSION IN MATRIX TERMS
PubH 745: REGRESSION ANALSIS REGRESSION IN MATRIX TERMS A mtr s dspl of umbers or umercl quttes ld out rectgulr rr of rows d colums. The rr, or two-w tble of umbers, could be rectgulr or squre could be
More informationunder the curve in the first quadrant.
NOTES 5: INTEGRALS Nme: Dte: Perod: LESSON 5. AREAS AND DISTANCES Are uder the curve Are uder f( ), ove the -s, o the dom., Prctce Prolems:. f ( ). Fd the re uder the fucto, ove the - s, etwee,.. f ( )
More informationExponential Generating Functions - J. T. Butler
Epoetal Geeatg Fuctos - J. T. Butle Epoetal Geeatg Fuctos Geeatg fuctos fo pemutatos. Defto: a +a +a 2 2 + a + s the oday geeatg fucto fo the sequece of teges (a, a, a 2, a, ). Ep. Ge. Fuc.- J. T. Butle
More informationare positive, and the pair A, B is controllable. The uncertainty in is introduced to model control failures.
Lectue 4 8. MRAC Desg fo Affe--Cotol MIMO Systes I ths secto, we cosde MRAC desg fo a class of ult-ut-ult-outut (MIMO) olea systes, whose lat dyacs ae lealy aaetezed, the ucetates satsfy the so-called
More informationParallel Newtonian Optimization without Hessian Approximation. Khalil K. Abbo College of Computer sciences and Mathematics University of Mosul
f. J. of Comp. & Mth s., Vol., No., 6 Pllel Newto Optmzto wthout ess Appomto Collee of Compute sceces d Mthemtcs Uvesty of Mosul eceved o: /9/5 Accepted o: 6//5 الملخص الغرض من هذا البحث هو اقتراح خوارزمية
More informationElastic-Plastic Transition of Transversely. Isotropic Thin Rotating Disc
otempoy Egeeg Sceces, Vol., 9, o. 9, 4-44 Elstc-Plstc sto o svesely Isotopc h ottg Dsc Sjeev Shm d Moj Sh Deptmet o Mthemtcs JII Uvesty, -, Secto 6 Nod-7, UP, Id sjt@edml.com, moj_sh7@edml.com stct Elstc-plstc
More informationFor use in Edexcel Advanced Subsidiary GCE and Advanced GCE examinations
GCE Edecel GCE Mthemtcs Mthemtcl Fomule d Sttstcl Tles Fo use Edecel Advced Susd GCE d Advced GCE emtos Coe Mthemtcs C C4 Futhe Pue Mthemtcs FP FP Mechcs M M5 Sttstcs S S4 Fo use fom Ju 008 UA08598 TABLE
More informationA Brief Introduction to Olympiad Inequalities
Ev Che Aprl 0, 04 The gol of ths documet s to provde eser troducto to olympd equltes th the stdrd exposto Olympd Iequltes, by Thoms Mldorf I ws motvted to wrte t by feelg gulty for gettg free 7 s o problems
More informationME 501A Seminar in Engineering Analysis Page 1
Mtr Trsformtos usg Egevectors September 8, Mtr Trsformtos Usg Egevectors Lrry Cretto Mechcl Egeerg A Semr Egeerg Alyss September 8, Outle Revew lst lecture Trsformtos wth mtr of egevectors: = - A ermt
More informationSequences and summations
Lecture 0 Sequeces d summtos Istructor: Kgl Km CSE) E-ml: kkm0@kokuk.c.kr Tel. : 0-0-9 Room : New Mleum Bldg. 0 Lb : New Egeerg Bldg. 0 All sldes re bsed o CS Dscrete Mthemtcs for Computer Scece course
More informationLinear Open Loop Systems
Colordo School of Me CHEN43 Trfer Fucto Ler Ope Loop Sytem Ler Ope Loop Sytem... Trfer Fucto for Smple Proce... Exmple Trfer Fucto Mercury Thermometer... 2 Derblty of Devto Vrble... 3 Trfer Fucto for Proce
More informationThe Z-Transform in DSP Lecture Andreas Spanias
The Z-Trsform DSP eture - Adres Ss ss@su.edu 6 Coyrght 6 Adres Ss -- Poles d Zeros of I geerl the trsfer futo s rtol; t hs umertor d deomtor olyoml. The roots of the umertor d deomtor olyomls re lled the
More informationSynthesis of Stable Takagi-Sugeno Fuzzy Systems
Sytess of Stle Tk-Sueo Fuzzy Systems ENATA PYTELKOVÁ AND PET HUŠEK Deptmet of Cotol Eee Fculty of Electcl Eee, Czec Teccl Uvesty Teccká, 66 7 P 6 CZECH EPUBLIC Astct: - Te ppe dels t te polem of sytess
More informationChapter Gauss-Seidel Method
Chpter 04.08 Guss-Sedel Method After redg ths hpter, you should be ble to:. solve set of equtos usg the Guss-Sedel method,. reogze the dvtges d ptflls of the Guss-Sedel method, d. determe uder wht odtos
More informationPreviously. Extensions to backstepping controller designs. Tracking using backstepping Suppose we consider the general system
436-459 Advnced contol nd utomtion Extensions to bckstepping contolle designs Tcking Obseves (nonline dmping) Peviously Lst lectue we looked t designing nonline contolles using the bckstepping technique
More informationQuestion 1. Typical Cellular System. Some geometry TELE4353. About cellular system. About cellular system (2)
TELE4353 Moble a atellte Commucato ystems Tutoal 1 (week 3-4 4 Questo 1 ove that fo a hexagoal geomety, the co-chael euse ato s gve by: Q (3 N Whee N + j + j 1/ 1 Typcal Cellula ystem j cells up cells
More informationParametric Methods. Autoregressive (AR) Moving Average (MA) Autoregressive - Moving Average (ARMA) LO-2.5, P-13.3 to 13.4 (skip
Pmeti Methods Autoegessive AR) Movig Avege MA) Autoegessive - Movig Avege ARMA) LO-.5, P-3.3 to 3.4 si 3.4.3 3.4.5) / Time Seies Modes Time Seies DT Rdom Sig / Motivtio fo Time Seies Modes Re the esut
More informationITERATIVE METHODS FOR SOLVING SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS
Numercl Alyss for Egeers Germ Jord Uversty ITERATIVE METHODS FOR SOLVING SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS Numercl soluto of lrge systems of ler lgerc equtos usg drect methods such s Mtr Iverse, Guss
More informationLecture 5 Single factor design and analysis
Lectue 5 Sngle fcto desgn nd nlss Completel ndomzed desgn (CRD Completel ndomzed desgn In the desgn of expements, completel ndomzed desgns e fo studng the effects of one pm fcto wthout the need to tke
More informationMulti-Electron Atoms-Helium
Multi-lecto Atos-Heliu He - se s H but with Z He - electos. No exct solutio of.. but c use H wve fuctios d eegy levels s sttig poit ucleus sceeed d so Zeffective is < sceeig is ~se s e-e epulsio fo He,
More informationCURVE FITTING LEAST SQUARES METHOD
Nuercl Alss for Egeers Ger Jord Uverst CURVE FITTING Although, the for of fucto represetg phscl sste s kow, the fucto tself ot be kow. Therefore, t s frequetl desred to ft curve to set of dt pots the ssued
More informationChapter I Vector Analysis
. Chpte I Vecto nlss . Vecto lgeb j It s well-nown tht n vecto cn be wtten s Vectos obe the followng lgebc ules: scl s ) ( j v v cos ) ( e Commuttv ) ( ssoctve C C ) ( ) ( v j ) ( ) ( ) ( ) ( (v) he lw
More informationAdvanced Higher Maths: Formulae
Advced Highe Mths: Fomule Advced Highe Mthemtics Gee (G): Fomule you solutely must memoise i ode to pss Advced Highe mths. Rememe you get o fomul sheet t ll i the em! Ame (A): You do t hve to memoise these
More informationLecture 11: Potential Gradient and Capacitor Review:
Lectue 11: Potentil Gdient nd Cpcito Review: Two wys to find t ny point in spce: Sum o Integte ove chges: q 1 1 q 2 2 3 P i 1 q i i dq q 3 P 1 dq xmple of integting ove distiution: line of chge ing of
More informationi+1 by A and imposes Ax
MASSACHUSETTS INSTITUTE OF TECHNOLOGY DEPARTMENT OF MECHANICAL ENGINEERING CAMBRIDGE, MASSACHUSETTS 09.9 NUMERICAL FLUID MECHANICS FALL 009 Mody, October 9, 009 QUIZ : SOLUTIONS Notes: ) Multple solutos
More informationOn EPr Bimatrices II. ON EP BIMATRICES A1 A Hence x. is said to be EP if it satisfies the condition ABx
Iteatoal Joual of Mathematcs ad Statstcs Iveto (IJMSI) E-ISSN: 3 4767 P-ISSN: 3-4759 www.jms.og Volume Issue 5 May. 4 PP-44-5 O EP matces.ramesh, N.baas ssocate Pofesso of Mathematcs, ovt. ts College(utoomous),Kumbakoam.
More informationThe Linear Probability Density Function of Continuous Random Variables in the Real Number Field and Its Existence Proof
MATEC Web of Cofeeces ICIEA 06 600 (06) DOI: 0.05/mateccof/0668600 The ea Pobablty Desty Fucto of Cotuous Radom Vaables the Real Numbe Feld ad Its Estece Poof Yya Che ad Ye Collee of Softwae, Taj Uvesty,
More informationSGN Audio and Speech Processing. Linear Prediction
SGN-46 Audo d Seech Poceg Le Pedcto Slde fo th lectue e bed o thoe ceted by Kt Mhoe fo TUT coue Puheeättely meetelmät Sg 3. Othe ouce: K. Koe: Puheeättely meetelmät, lectue mtel, TUT, htt://www.c.tut.f/coue/sgn-4/g4.df
More informationPhysics 604 Problem Set 1 Due Sept 16, 2010
Physics 64 Polem et 1 Due ept 16 1 1) ) Inside good conducto the electic field is eo (electons in the conducto ecuse they e fee to move move in wy to cncel ny electic field impessed on the conducto inside
More informationDEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING FLUID MECHANICS III Solutions to Problem Sheet 3
DEPATMENT OF CIVIL AND ENVIONMENTAL ENGINEEING FLID MECHANICS III Solutions to Poblem Sheet 3 1. An tmospheic vote is moelle s combintion of viscous coe otting s soli boy with ngul velocity Ω n n iottionl
More informationStructure from Motion Using Optical Flow Probability Distributions
Stuctue om Moto sg Optcl Flow Polt Dstutos Pul Meell d D. J. Lee Deptmet o Electcl d Compute Egeeg Bghm Youg vest 459 CB Povo th 846 ABSRAC Stuctue om moto s techque tht ttempts to ecostuct the 3D stuctue
More informationCBSE SAMPLE PAPER SOLUTIONS CLASS-XII MATHS SET-2 CBSE , ˆj. cos. SECTION A 1. Given that a 2iˆ ˆj. We need to find
BSE SMLE ER SOLUTONS LSS-X MTHS SET- BSE SETON Gv tht d W d to fd 7 7 Hc, 7 7 7 Lt, W ow tht Thus, osd th vcto quto of th pl z - + z = - + z = Thus th ts quto of th pl s - + z = Lt d th dstc tw th pot,,
More information6. Chemical Potential and the Grand Partition Function
6. Chemcl Potetl d the Grd Prtto Fucto ome Mth Fcts (see ppedx E for detls) If F() s lytc fucto of stte vrles d such tht df d pd the t follows: F F p lso sce F p F we c coclude: p I other words cross dervtves
More informationWe show that every analytic function can be expanded into a power series, called the Taylor series of the function.
10 Lectue 8 We show tht evey lytic fuctio c be expded ito powe seies, clled the Tylo seies of the fuctio. Tylo s Theoem: Let f be lytic i domi D & D. The, f(z) c be expessed s the powe seies f( z) b (
More informationsuch that for 1 From the definition of the k-fibonacci numbers, the firsts of them are presented in Table 1. Table 1: First k-fibonacci numbers F 1
Scholas Joual of Egeeg ad Techology (SJET) Sch. J. Eg. Tech. 0; (C):669-67 Scholas Academc ad Scetfc Publshe (A Iteatoal Publshe fo Academc ad Scetfc Resouces) www.saspublshe.com ISSN -X (Ole) ISSN 7-9
More informationSEPTIC B-SPLINE COLLOCATION METHOD FOR SIXTH ORDER BOUNDARY VALUE PROBLEMS
VOL. 5 NO. JULY ISSN 89-8 RN Joul of Egeeg d ppled Sceces - s Resech ulshg Netok RN. ll ghts eseved..pouls.com SETIC -SLINE COLLOCTION METHOD FOR SIXTH ORDER OUNDRY VLUE ROLEMS K.N.S. Ks Vsdhm d. Mul Ksh
More informationAn Improved Wavefront Control Algorithm for Large Space Telescopes
A Impoved Wvefot Cotol Algothm fo Lge Spce Telescopes Ek Sdck*, Scott A. Bsge, d Dvd C. Reddg Jet Populso Lbotoy, Clfo Isttute of Techology, 48 Ok Gove Dve, Psde, CA, USA 99 ABSTRACT Wvefot sesg d cotol
More informationSummary: Binomial Expansion...! r. where
Summy: Biomil Epsio 009 M Teo www.techmejcmth-sg.wes.com ) Re-cp of Additiol Mthemtics Biomil Theoem... whee )!!(! () The fomul is ville i MF so studets do ot eed to memoise it. () The fomul pplies oly
More informationSoo King Lim Figure 1: Figure 2: Figure 3: Figure 4: Figure 5: Figure 6: Figure 7: Figure 8: Figure 9: Figure 10: Figure 11:
Soo Kg Lm 1.0 Nested Fctorl Desg... 1.1 Two-Fctor Nested Desg... 1.1.1 Alss of Vrce... Exmple 1... 5 1.1. Stggered Nested Desg for Equlzg Degree of Freedom... 7 1.1. Three-Fctor Nested Desg... 8 1.1..1
More information